🧠 Test Automation Engineer Agent Specification¶

🎯 Purpose¶

The Test Automation Engineer Agent is responsible for:

Orchestrating, executing, monitoring, and reporting automated tests across all layers of the platform — transforming static test artifacts into fully operational, edition-aware, CI/CD-integrated test pipelines.

It ensures that all generated tests from other agents (like Test Case Generator and Test Generator) are:

✅ Executed correctly across relevant roles, editions, and environments
🧪 Validated continuously during builds, merges, and releases
📊 Reported back into Studio and observability dashboards
🛠️ Maintained through retries, environment prep, and isolation strategies

🧱 What Sets It Apart from Other QA Agents?¶

Agent	Primary Role
🧪 Test Case Generator	Creates static `.cs`, `.feature`, and test metadata files
🧠 Test Generator	Expands test coverage based on prompts, gaps, and behavior
⚙️ Test Automation Engineer Agent	Runs the tests, connects them to pipelines, interprets results, manages environments
📈 Test Coverage Validator Agent	Measures static and dynamic test coverage
👤 QA Engineer Agent	Guides strategy, approves coverage, collaborates via Studio

🔧 Responsibilities in Factory Flow¶

Executes all test types: unit, integration, BDD, security, performance
Chooses which tests to run per pipeline context (pre-merge, nightly, release)
Manages runtime environments, mocks, and infrastructure dependencies
Collects results, logs, screenshots, and traces
Validates test completeness against trace/edition coverage targets
Reports status and regressions into:
- Studio dashboards
- Pull Request annotations
- QA and CI/CD artifacts

🧠 Factory Blueprint: Execution Lifecycle¶

flowchart TD
    A[TestCaseGeneratorAgent] --> B[TestArtifacts]
    B --> C[TestAutomationEngineerAgent]
    C --> D[TestExecutionPlan]
    D --> E[TestExecution]
    E --> F[TestResults]
    F --> G[StudioDashboard]
    F --> H[TestCoverageValidatorAgent]

Hold "Alt" / "Option" to enable pan & zoom

✅ It is the execution orchestrator of the QA pipeline.

📘 Example Responsibilities¶

Given:

.feature file: create_invoice.feature
Unit test: CreateInvoiceHandlerTests.cs
Metadata: edition = enterprise, roles = [FinanceManager, Guest]
Trigger: PR pre-merge validation

Agent will:

Plan edition-specific execution matrix
Select runner (SpecFlow, dotnet test, Playwright, etc.)
Provision test config for enterprise edition with mocks
Run test with FinanceManager and Guest roles
Collect results
Attach results to Studio + PR + CI

🔁 Continuous Role¶

This agent stays active throughout:

🔁 Pre-commit test validation
🧪 Nightly test runs
🚀 Pre-release quality gates
🔍 Studio feedback and rerun triggers
🔁 Rerun failed test suites with new configuration

✅ Summary¶

The Test Automation Engineer Agent is the backbone of operational QA automation, ensuring that:

💡 All generated tests become running tests
🔄 Test plans adapt to edition, role, environment
🧪 Results flow back into the Studio and feedback loops
📎 Everything is trace-tagged, observable, and CI-ready

It transforms ConnectSoft's QA system from static test definitions into a living, self-updating quality automation mesh.

🏗️ Strategic Role in the Factory¶

The Test Automation Engineer Agent is the operational executor and runtime orchestrator in the QA Engineering Cluster. It connects test creation (definition) with test validation (execution) in the factory pipeline.

It ensures that all test artifacts — regardless of how or where they were generated — are executed:

📦 Across environments
🔁 Across roles and editions
🧪 Within CI/CD gates
🧠 With traceable feedback into Studio and QA agents

🧩 Position in Factory Cluster Topology¶

🔄 QA Engineering Cluster¶

flowchart TD
    subgraph QA Engineering Agents
        A[Test Case Generator Agent]
        B[Test Generator Agent]
        C[Test Coverage Validator Agent]
        D[Test Automation Engineer Agent]
        E[QA Engineer Agent]
    end

    A --> D
    B --> D
    D --> C
    D --> E
    C --> E

Hold "Alt" / "Option" to enable pan & zoom

🔁 CI/CD Pipeline Integration Points¶

flowchart TD
    CodeCommit --> Generate[Test Generation]
    Generate --> TestPlan[TestExecutionPlan.yaml]
    TestPlan --> TestRun[Test Automation Engineer Agent]
    TestRun --> Results[TestResults + Logs]
    Results --> QAReview[Studio + QA Feedback]
    Results --> Coverage[Test Coverage Validator Agent]

Hold "Alt" / "Option" to enable pan & zoom

🎯 Pipeline Touchpoints¶

Stage	Test Automation Engineer Agent Role
🛠 Pre-Build	Validates if any test setup/mocks need to be injected
🧪 Build & Test	Runs unit tests, integration tests, BDDs
🔁 Retry on Failure	Re-runs quarantined or flaky tests
🚦 Quality Gate	Emits result summaries, thresholds
📥 Pre-PR Merge	Annotates test results in Git PR
🧾 Post-Release	Executes long-running validations or scheduled test jobs
🧠 Bug Reproduction	Re-runs tests related to failed production traces or bug triggers

📦 Factory Context: Service Edition & Role Flow¶

The agent sits at the intersection of QA artifacts and execution environments.

Input	Source Agent	Consumption
`.feature`, `.cs`	Test Case/Test Generator Agents	Schedules test run
`test-metadata.yaml`	Generator Agents	Builds test plan matrix
`Studio prompt`	QA Agent	Replays or triggers test
`trace_id + edition`	Blueprint + CI	Isolates test context
`qa-plan.yaml`	QA Engineer Agent	Orchestrates which sets must run in this build

🧠 Real-Time Role in Studio¶

Monitors trace coverage gaps
Responds to "Rerun with new edition config" requests
Logs scenario results into the UI per edition/role combo
Sends test failures → bug resolver or retry system

📘 Sample Workflow: Pull Request¶

Developer commits new handler
Test Case Generator adds CreateInvoiceHandlerTests.cs
Test Generator adds .feature for Guest role
Test Automation Engineer Agent:
- Selects edition: enterprise
- Executes .feature scenarios + unit test with role matrix
- Collects logs and reports
- Posts PR comment:
  
  ✅ 6 tests passed ❌ 1 test failed for Guest role → opened retry job

✅ Summary¶

The Test Automation Engineer Agent is strategically positioned to:

Operate at the boundary of test design and test validation
Connect generation with runtime execution across editions
Power Studio insights, QA metrics, and CI test reliability
Serve as the automated executor and verifier in ConnectSoft’s QA flow

📋 Responsibilities¶

The Test Automation Engineer Agent owns the end-to-end orchestration of test execution, from planning which tests to run, to executing them across environments and roles, to reporting results with full traceability.

Its goal is to ensure that all tests produced in the factory are continuously validated, observable, reproducible, and reliable.

✅ Key Responsibilities Breakdown¶

Responsibility	Description
1. Execute All Test Types	Runs unit tests, integration tests, BDD `.feature` scenarios, security tests, edge cases
2. Apply Edition + Role Context	Executes tests with edition-specific configuration and per-role identity injection
3. Orchestrate CI/CD Test Runs	Integrates with Azure DevOps (or other CI), runs during build, PR, and release
4. Monitor Test Results	Collects pass/fail states, logs, telemetry, screenshots (for UI/e2e)
5. Handle Retries and Quarantine	Re-runs flaky or failed tests and marks unstable ones for investigation
6. Generate Test Execution Plan	Uses `test-metadata.yaml` and QA plan files to construct dynamic run sets
7. Enforce Test Execution Policies	Applies timeouts, concurrency rules, isolation modes, and system constraints
8. Emit Execution Metrics	Publishes results and execution stats to Studio, QA reports, and dashboards
9. Trace Result Back to Test Generator	Links results to originating generator, trace ID, edition, role, handler
10. Integrate with Studio	Shows real-time and historical test results, role/edition matrix views, retry buttons
11. Support Manual Triggers from QA	Allows on-demand test execution per trace, scenario, edition, or prompt
12. Schedule Tests	Runs tests at regular intervals (e.g., nightly regression, weekly release blockers)
13. Provide Failure Context	Logs, screenshots, span traces, and output are made available for debugging
14. Generate Artifacts	Produces `.trx`, `.xml`, `.json`, and Markdown reports for every test run
15. Monitor Resource Usage	Optimizes test execution for parallelism and execution time tracking
16. Support Cross-Service Integration Tests	Coordinates with other services or mocks where needed
17. Handle Edition/Feature Toggles	Injects correct feature flags or behavior constraints before execution
18. Maintain Observability Hooks	Emits OpenTelemetry spans and error metrics for each test run
19. Recover from Failures Gracefully	Runs retries, captures logs, and prevents blocking unrelated pipelines
20. Validate Test Definitions Before Execution	Ensures test is syntactically and structurally valid before run time

🎯 Responsibility Scope vs. Other QA Agents¶

Capability	Generator Agents	Test Automation Engineer Agent
Test Definition	✅	❌
Test Expansion	✅	❌
Test Execution	❌	✅
CI/CD Orchestration	❌	✅
Retry Handling	❌ (except for prompt-level)	✅
Logs, Artifacts, Dashboards	❌	✅
Trace Tagging, Assertion Monitoring	Partial	Full runtime span capture

📘 Real-World Execution Example¶

For handler CapturePaymentHandler, with these generated files:

CapturePaymentHandlerTests.cs
capture_payment.feature
test-metadata.yaml

And this edition context:

edition: enterprise
roles: [Cashier, Guest]

The agent will:

Generate matrix of (role, edition) pairs
Inject enterprise configuration into the test environment
Set identity to Cashier → run unit and .feature tests
Repeat with Guest role
Record pass/fail logs per step
Emit Studio summary and CI/CD job artifact
If Guest fails with 403, send retry trigger to QA workflow

✅ Summary¶

The Test Automation Engineer Agent transforms ConnectSoft’s tests from static artifacts into:

🧪 Live, continuous, traceable executions
📊 Measurable QA results with studio visibility
🚦 Reliable CI/CD signals that validate quality gates
🔁 Retryable, observable, and role/edition-specific feedback loops

This ensures that quality is enforced, not assumed, across the entire software factory lifecycle.

📥 Inputs¶

To execute tests intelligently and reliably, the Test Automation Engineer Agent consumes a multi-source set of inputs from upstream agents, CI pipelines, configuration files, and Studio.

These inputs allow it to:

📋 Know what to run
🧪 Determine how and where to run it
🎯 Apply context: trace, edition, roles, feature flags
🔄 Support retry logic, execution control, and observability hooks

📦 Primary Inputs by Type¶

Input Type	Description	Source
Test Artifacts	`.cs`, `.feature`, step definitions, test classes	Test Case Generator / Test Generator
Test Metadata	`test-metadata.yaml`, `test-augmentation-metadata.yaml`	Generator Agents
Trace Context	`trace_id`, `handler_name`, `edition`, `roles`, `blueprint_id`	Blueprint, Generator Agents
QA Plan Definitions	`qa-plan.yaml` per microservice or feature cluster	QA Engineer Agent
CI/CD Trigger Metadata	Pipeline ID, PR ID, environment, build scope	Azure DevOps / GitHub Actions
Studio Prompts or Actions	Manual rerun request, trace-specific execution	Studio (QA UI)
Test Matrix Templates	Role × Edition × Scenario pairing logic	Factory test matrix schema
Environment Variables & Secrets	Edition config, identity injection, mocked services	Config Services / Secrets Store
Test Execution Constraints	Timeouts, max retries, parallel limits, tags to skip	Config files + QA Agent input
Memory Lookups (optional)	Past test runs for trace-aware diff coverage	Memory + History Service
Bug Trace or Rerun Request	Replay test case linked to past bug ID	Bug Resolver Agent or Studio

🧩 Example: `test-metadata.yaml`¶

trace_id: capture-2025-0281
blueprint_id: usecase-9361
module: PaymentsService
handler: CapturePaymentHandler
roles_tested: [Cashier, Guest]
test_cases:
  - type: unit
    file: CapturePaymentHandlerTests.cs
  - type: bdd
    file: capture_payment.feature
  - type: validator
    file: CapturePaymentValidatorTests.cs
edition_variants: [enterprise, lite]

→ Agent builds execution plan:

Run .cs and .feature files
For Cashier and Guest
In both enterprise and lite editions

🧠 Input: QA Execution Plan¶

service: PaymentsService
build_type: pull_request
required_tests:
  - all unit
  - all BDD tagged @security
  - edition-specific scenarios for @enterprise
optional_tests:
  - validator
  - duplicate scenarios (marked @retired)

→ Determines filtering and prioritization of what will be run for the build step.

📘 Input: Studio Manual Trigger¶

{
  "action": "rerun",
  "trace_id": "invoice-2025-0147",
  "edition": "enterprise",
  "role": "Guest",
  "scenario": "Guest tries to approve invoice"
}

→ Agent re-executes only the matching .feature scenario under specified context.

🔍 Environment Inputs¶

Variable	Used For
`EDITION=enterprise`	Injects config toggles, flags, mocks
`USER_ROLE=Guest`	Sets identity or token for test runner
`TEST_RUN_ID=build_4871`	Traceability
`QA_TRIGGER_SOURCE=studio.manual`	Audit trails and retry tagging
`FEATURE_FLAGS_ENABLED=true`	Enables toggled behaviors in runtime
`ISOLATE_TESTS=true`	Enforces containerized test environment

✅ Summary¶

The Test Automation Engineer Agent consumes a comprehensive and trace-rich input graph that includes:

🔧 All test assets from factory generation
🧪 Execution instructions, constraints, roles, editions
🎛️ Environment config and identity injection
📎 Trace-aware hooks for audit, retry, and QA validation

This gives it the flexibility and intelligence to run only what matters, while maintaining full traceability and CI compliance.

📤 Outputs¶

The Test Automation Engineer Agent transforms static test artifacts and trace metadata into executed results, runtime logs, and trace-linked feedback.

Its outputs are designed to:

📊 Feed Studio dashboards with result status
📁 Generate detailed test reports and logs for CI/CD
📎 Maintain traceability back to trace_id, edition, role, and blueprint
🔁 Support retries, analysis, and coverage deltas

📦 Primary Output Artifacts¶

Output Type	Description	Format/Example
Test Results	Pass/fail status for each test executed	`.trx`, `.json`, `.xml`, Markdown
Test Execution Summary	High-level run result per trace/handler	`test-execution-summary.yaml`
Test Logs	Output from test runners, assertions, stack traces	`.log`, `.txt`
Screenshots & Traces	UI or system-level artifacts for failures	`.png`, `.har`, `.trace.json`
Coverage Delta Reports	Before/after snapshot of role/scenario coverage	`trace-coverage-diff.yaml`
QA Report Files	Human-readable reports pushed to Studio	`qa-execution-report.md`
Observability Events	OTel spans, test-level metrics and logs	`test-execution-events.jsonl`
Retry Metadata	Captures retry attempts and success/failure status	`execution-retry-history.yaml`

📘 Example: Test Execution Summary¶

trace_id: invoice-2025-0147
handler: CreateInvoiceHandler
edition: enterprise
roles_executed:
  - FinanceManager
  - Guest
summary:
  total_tests: 6
  passed: 5
  failed: 1
  retries: 1
  duration_seconds: 27.4
last_run_at: 2025-05-17T12:44:09Z
report_files:
  - invoice_trace0147_execution.trx
  - test-output.log
  - qa-execution-report.md

🧠 Markdown QA Report Output¶

### 🧪 Test Execution Report — CreateInvoiceHandler

📎 Trace: invoice-2025-0147  
🏷️ Edition: enterprise  
🎭 Roles Tested: FinanceManager, Guest

✅ Passed:
- Handle_ShouldReturnSuccess_WhenValidInput
- Scenario: Successful invoice creation

❌ Failed:
- Scenario: Guest attempts invoice approval  
  Reason: StatusCode was 200, expected 403

🔁 Retry Attempt: ✅ Success on second run  
📘 Trigger: Pre-merge CI pipeline  
📦 Artifacts: `invoice-2025-0147.trx`, `guest-403.log`

📊 Observability Output (JSONL Span Log)¶

{
  "event": "TestExecuted",
  "trace_id": "invoice-2025-0147",
  "role": "Guest",
  "scenario": "Guest attempts invoice approval",
  "status": "failed",
  "status_code": 200,
  "expected_code": 403,
  "duration_ms": 420,
  "retried": true
}

→ Ingested by Studio + Monitoring dashboards

📁 File Output Directory (example)¶

/test-results/
├── invoice-2025-0147/
│   ├── qa-execution-report.md
│   ├── invoice-2025-0147.trx
│   ├── guest-403.log
│   ├── invoice-2025-0147.trace.json
│   └── test-execution-summary.yaml

📎 Traceability Metadata¶

Each test result includes:

augmented_by: test-automation-engineer-agent
source_trace_id: invoice-2025-0147
generated_from: CreateInvoiceHandlerTests.cs
executed_roles: [Guest]
edition: enterprise
execution_status: failed
retry_count: 1

🔄 Output Triggers for Other Agents¶

Agent	Triggered By
Bug Resolver Agent	Test failure with trace → emits reproduction workflow
Test Coverage Validator Agent	Coverage delta report → updates scenario heatmap
Pull Request Creator Agent	Pass/fail status → PR comment annotations
QA Engineer Agent	Markdown + artifact summary → integrated into test plan reviews
Studio	Real-time display of test outcome per role + edition

✅ Summary¶

The Test Automation Engineer Agent emits:

📊 Machine-readable results (.trx, .json)
📘 Human-readable markdown reports
📈 Execution summaries for trace/handler/role/edition
🧪 Logs, artifacts, and retry metadata
🔁 Events and observability spans for feedback loops

This ensures that every test produced by the factory is verifiably executed, auditable, and explorable by humans and machines.

🧪 Supported Test Types and Runners¶

The Test Automation Engineer Agent supports execution of all test types produced by the ConnectSoft factory:

✅ Unit tests
✅ Integration tests
✅ BDD/Scenario tests
✅ Validator/FluentValidation tests
✅ Security and access control tests
✅ Retry, resiliency, and chaos scenario validations
✅ Edition-variant test paths
✅ Prompt-augmented edge and AI-generated cases

Each test type is executed using the appropriate test runner, identity injection, and configuration context.

📦 Supported Test Types¶

Test Type	Description	Source
Unit Tests	Test `IHandle<T>` logic in isolation with mocks	`.cs` via Test Case Generator
Validator Tests	Test FluentValidation rules in DTOs	`.cs` via Test Case Generator
Integration Tests	Run HTTP/gRPC endpoints in test host	`.cs`, `WebApplicationFactory`
BDD Scenario Tests	Run `.feature` files + `Steps.cs` via SpecFlow	Test Generator
Security Role Tests	Assert behavior under different roles/claims	Scenario + Role Matrix
Negative & Edge Case Tests	Handle nulls, invalid values, format issues	AI-generated `.cs` + `.feature`
Edition-Aware Scenarios	Tests scoped to specific feature toggles	Edition variants in `.feature`
Performance Hooks (Optional)	Smoke & runtime diagnostics	BDD + scenario timer tags
Replay & Regression Tests	Tests triggered from bug trace	Bug Resolver / Studio Manual
Manual Triggered Tests	Executed on demand from Studio trace view	QA Prompt or QA Plan

🧰 Test Runners and Tools Used¶

Runner	Test Type	Integration
`dotnet test`	Unit, validator, integration	MSTest, xUnit
`SpecFlow CLI`	`.feature` + `Steps.cs`	Scenario tests
`Playwright` or `Cypress` (Optional)	End-to-end UI	For web-scenario validation
`Azure DevOps Test Tasks`	CI/CD orchestration	Hosted agents
`FeatureToggleHarness`	Simulates edition-based configurations	Injects runtime context
`TestIsolationExecutor`	Runs scenarios in isolated containers for concurrency	Parallel test runs
`RoleInjectionRunner`	Wraps test runs in identity context (JWT, headers, claims)	Security scenario execution

📘 BDD Scenario Execution¶

For a .feature file like:

Scenario: Guest cannot cancel invoice
  Given the user is Guest
  When they submit a cancel request
  Then the system returns 403 Forbidden

Agent uses:

✅ SpecFlow test runner
✅ enterprise config injected
✅ Guest token generated
✅ Scenario executed in parallel run

Outputs:

✅ Passed or Failed
✅ Studio shows result and trace ID
✅ CI pipeline validates pre-merge status

🧩 Execution by Scenario Tags¶

The agent dynamically selects test cases using tags:

Tag	Action
`@role:CFO`	Sets identity as CFO
`@edition:lite`	Injects feature flags/config for lite edition
`@security`	Prioritized in pre-release checks
`@retry`	Rerun until successful or marked unstable
`@prompt_generated`	Runs with explanation markdown included
`@performance`	Measures step duration and total scenario time

🎯 Real-World Example Execution Plan¶

trace_id: refund-2025-0143
handler: IssueRefundHandler
roles: [SupportAgent, Guest]
edition: enterprise
test_types:
  - unit: IssueRefundHandlerTests.cs
  - bdd: refund_flow.feature
execution_matrix:
  - edition: enterprise
    role: SupportAgent
  - edition: enterprise
    role: Guest
runners_used:
  - dotnet test
  - SpecFlow CLI
identity: jwt injected
env_config: edition-enterprise.json

✅ Summary¶

The Test Automation Engineer Agent supports a wide range of test types and execution strategies, including:

🎯 Precision selection by role and edition
🧪 Rich support for both .cs-based and .feature-based test flows
🧠 Handling of intelligent, AI-suggested edge and security tests
📦 Runner selection that matches the architecture: MSTest, SpecFlow, Playwright, etc.
📎 All runs are trace-tagged, version-aware, and CI-integrated

This flexibility ensures every type of test generated by the factory can be executed, validated, and reported — reliably and observably.

🎯 Edition- and Role-Aware Test Execution Planning¶

One of the Test Automation Engineer Agent’s most powerful capabilities is its ability to execute the same test logic under different editions and roles, enabling:

✅ Validation of feature toggles and edition-specific behavior
🔐 Testing of role-based access control paths (success, rejection, escalation)
📎 Traceability of behavior per edition and user identity
📘 Proper QA coverage across multi-tenant, multi-tier SaaS configurations

🧩 Key Execution Concepts¶

Dimension	Description
Edition Awareness	Executes tests in different product tiers (`lite`, `pro`, `enterprise`) by injecting config, flags, mocks
Role Awareness	Wraps test executions in identity contexts (claims, JWTs, headers) to simulate real user roles
Matrix Execution	Builds `edition × role` matrix per test case and executes each variant independently
Test Grouping	Batches tests into parallelizable segments per edition/role pair
Trace Result Aggregation	Tags and stores test results per `trace_id`, `edition`, and `role`, enabling Studio dashboards to reflect fine-grained outcomes

🧬 Execution Matrix Example¶

For the following scenario:

Handler: CancelInvoiceHandler
Editions: lite, enterprise
Roles: FinanceManager, CFO, Guest

Agent builds this plan:

Edition	Role	Action
`lite`	`FinanceManager`	Run unit + `.feature`
`lite`	`Guest`	Run `.feature` → expect `403`
`enterprise`	`CFO`	Run unit + `.feature`
`enterprise`	`Guest`	Run `.feature` → expect `403`

Total test executions: 4 variants

⚙️ How Agent Applies Edition Context¶

Step	Action
1. Load `edition` config	Reads flags from `edition-enterprise.json`
2. Inject runtime env	Passes config to test host, DI container, or service harness
3. Override mocks	Enables/disables behaviors based on edition toggles
4. Set test tag context	Tags test results with edition in metadata and Studio
5. Record outcomes per edition	Stores results for dashboards, deltas, and trace views

🔐 Role Injection Flow¶

Role Type	Injection Strategy
JWT Claims	`role=FinanceManager`, `scope=invoice.write`
Header	`x-user-role: CFO`
CLI Arg	`--role Guest` passed to test runner
DI Overload	Injects identity context into handlers/controllers

Agent ensures identity is enforced at:

Test framework level (for BDD steps)
HTTP/gRPC request level (for integration tests)
Middleware/auth policies during in-process tests

📘 Output Metadata per Variant¶

trace_id: invoice-2025-0147
handler: CancelInvoiceHandler
executed_roles:
  - Guest
  - CFO
  - FinanceManager
edition: enterprise
scenario: Cancel invoice after approval
results:
  - role: Guest
    edition: enterprise
    result: failed
    reason: expected 403, got 200
  - role: CFO
    edition: enterprise
    result: passed

📊 Studio Dashboard View¶

Scenario	Guest (lite)	Guest (enterprise)	CFO (enterprise)
Cancel after approval	✅ Forbidden (403)	❌ Unexpected 200	✅ Approved

→ Red cell triggers QA review or re-gen from Test Generator Agent.

🧠 Adaptive Execution Planning¶

The agent automatically:

Skips unneeded editions/roles if already covered
Merges overlapping editions if config is equivalent
Prioritizes @security-tagged roles in pre-release runs
Schedules missing variants flagged by Test Coverage Validator Agent

✅ Summary¶

The Test Automation Engineer Agent executes all tests using a matrix of editions and roles, ensuring:

📦 Multi-tier SaaS configurations are fully covered
🔐 Access control paths are enforced and validated
📎 Results are traceable by edition/role per test
📊 QA and Studio benefit from full-spectrum observability

This capability is essential for validating multi-tenant, feature-variant, role-sensitive SaaS platforms like those produced by ConnectSoft AI Software Factory.

🔁 Pipeline Integration (CI/CD, Pre-Merge, Release Gates)¶

The Test Automation Engineer Agent isn’t just a test executor — it’s a test execution orchestrator for factory pipelines. It ensures that all generated tests:

🧪 Run at the right stage (PR, build, release, nightly)
🚦 Block or permit deployment based on test results
📎 Report to the right systems (Studio, QA reports, Azure DevOps)
🔁 Rerun selectively in case of failure or QA request
🧱 Respect edition, role, scope, and test type constraints

🧩 Key CI/CD Integration Responsibilities¶

Stage	Agent Responsibility
Pre-Build	Validates test folders, prepares edition config/mocks
Build/PR	Executes unit + BDD + security tests for scope of change
Post-Build / Coverage Check	Compares what ran vs. what was expected
Pre-Release	Runs full matrix (editions × roles × scenarios)
Nightly / Scheduled	Executes slow, full, exploratory, or randomized sets
On-Demand	Supports Studio-triggered re-runs or trace validation jobs
Test Coverage Validator Hooks	Feeds actual run data into gap analysis
Pull Request Integration	Annotates PRs with test summary and trace status
Release Gate	Blocks pipeline if regressions, failures, or coverage drop below threshold

📘 Sample CI/CD Pipeline Structure¶

- stage: BuildAndTest
  jobs:
    - job: UnitTests
      steps:
        - run: dotnet test Payments.UnitTests.csproj
        - publish: *.trx

    - job: BDDTests
      steps:
        - run: specflow run refund_flow.feature --edition=enterprise --role=Guest
        - publish: *.json

    - job: StudioReport
      steps:
        - run: agent generate-qa-report --trace invoice-2025-0147
        - publish: qa-execution-report.md

→ Agent controls test runner invocation, context injection, and result publication.

📊 Agent Output → PR Annotation Example¶

📎 Trace: invoice-2025-0147
✅ 6 tests passed | ❌ 1 failed (Guest role, edition=enterprise)
🔁 Retry: success on 2nd attempt
📘 Report: /test-results/invoice-2025-0147/qa-execution-report.md

🚦 Release Gates Example¶

Agent emits thresholds:

required_coverage:
  roles: 100%
  editions: 100%
  @security: all must pass

allow_if:
  unstable_scenarios < 2
  retries < 3

→ Fails the gate if @security scenario for Guest returns 200 instead of 403.

🧠 Pipeline-Aware Execution Scoping¶

Change Detected	Action
Handler changed	Only run tests with that `trace_id`
Edition config updated	Run edition-specific `.feature` only
DTO structure changed	Run validator + integration tests
Role added to access map	Run security scenarios across new role
Studio prompt	Rerun trace-scenario on demand

🧾 Outputs Stored in CI¶

File	Description
`*.trx`	MSTest/XUnit result output
`*.json`	SpecFlow/BDD structured test output
`qa-execution-report.md`	Human-readable QA result summary
`test-execution-summary.yaml`	Machine-readable pipeline trace
`retry-metadata.json`	Retry history and resolution status

🧠 Studio & DevOps Integration¶

Feature	Outcome
🔁 Retry failed test	Run single scenario via trace ID
📎 Link test → PR	Add trace result to Git PR comment
📊 Studio dashboard updates	Show edition/role matrix from actual execution
🧪 Execution delta detection	Only run what changed (intelligent scoping)

✅ Summary¶

The Test Automation Engineer Agent integrates seamlessly into CI/CD by:

🧪 Running the right tests at the right stage
📎 Reporting test status per trace, role, and edition
🚦 Enforcing gates for regressions and coverage
🔁 Supporting retries, replays, and QA-initiated flows
📘 Publishing human- and machine-readable results across platforms

This ensures that every pipeline in the ConnectSoft Factory is quality-enforced, trace-driven, and test-aware by design.

🎯 Test Suite Composition and Selection Strategy¶

The Test Automation Engineer Agent must not run everything on every build — it must select the most relevant and trace-aligned tests based on:

💡 What changed (code, edition config, roles)
📦 What trace ID or module was triggered
📊 Which tests cover the affected paths
🚦 What QA policy, prompt, or CI gate applies
🧠 What has already been tested and validated

This results in precise, efficient, edition-aware test execution optimized for both velocity and quality.

📦 What a Test Suite Consists Of¶

Element	Description
Test Units	Individual test methods or `.feature` scenarios
Execution Targets	Role × Edition × Scenario variants
Runner Context	Identity injection, env overrides, edition flags
Tags/Scopes	e.g. `@security`, `@regression`, `@edge`
Test Type	Unit, BDD, Validator, Integration, Replay, Prompt-based
Priority Level	High (pre-merge), Medium (post-build), Low (nightly)

🧩 Strategy for Test Suite Selection¶

1. Trace-Aware Matching¶

If trace_id: cancel-2025-0142 was generated, select:
- All .cs tests from CancelInvoiceHandlerTests.cs
- All scenarios from cancel_invoice.feature
- Role/edition combinations listed in test-metadata.yaml

2. Tag-Based Inclusion¶

Select all scenarios with:
- @security → enforced in all editions
- @prompt_generated → always run once
- @chaos, @retry → scheduled or nightly only

3. Edition/Role Expansion¶

If edition = pro and role = CFO, auto-expand .feature scenarios tagged:
- @edition:pro
- @role:CFO
- Default (@edition:all or untagged)

4. Change-Based Diff Scoping¶

Code diff touches:
- CreateInvoiceHandler.cs → select unit tests + .feature mapped via trace
- edition-enterprise.json → select edition-sensitive scenarios

5. QA Plan Inclusion¶

qa-plan.yaml defines:

required_tests:
  - all @security
  - all @edition:enterprise
  - minimum 1 per handler

6. Bug Trace Replay¶

Bug #4281 marked CustomerId = null
- Find all matching failed traces
- Rerun only affected .feature scenarios + validator tests

📘 Test Selection YAML Snapshot¶

execution_scope:
  trace_id: cancel-2025-0142
  selected_tests:
    - CancelInvoiceHandlerTests.cs
    - cancel_invoice.feature
  roles: [CFO, Guest]
  editions: [lite, enterprise]
  tags_required: [security]
  sources: [test-generator, test-case-generator]

🔍 Test Exclusion Logic¶

Reason	Exclusion
Scenario tagged `@retired`	Not executed
Marked as `flaky` in retry log	Deferred to nightly job
Role not supported in edition	Skipped with note
Already passed in current pipeline context	Reuse result unless override requested

🎛️ Studio-Controlled Scope Override¶

Studio allows:

Manual trace re-run (specific handler + scenario)
Edition re-simulation
“Run only security scenarios for this handler”
Prompt-based scope trigger → selects only new prompt scenarios

✅ Summary¶

The Test Automation Engineer Agent composes test suites dynamically by:

🧠 Selecting only what’s relevant based on trace, diff, tags, edition, and role
📦 Using QA plans, change diffs, and test metadata to optimize scope
📘 Ensuring all tests run in the correct configuration context
🔁 Allowing full traceability and replay from Studio or CI events

This strategy keeps execution fast, relevant, and intelligent across all QA pipelines.

🎯 Failure Handling, Retries, and Quarantining Logic¶

Even well-defined tests fail — due to:

🚫 Intermittent infrastructure issues
🔄 Flaky behavior
🔒 Authorization mismatch
🧠 Logic or data regressions
🧪 Newly introduced bugs

The Test Automation Engineer Agent handles failures through a controlled, trace-aware, and observable retry + quarantine system that ensures:

🔁 Legitimate bugs are surfaced
⚠️ Flaky tests are isolated, not ignored
🛡️ Release gates are protected from noise
📎 Trace logs, retries, and failures are audit-safe

🔁 Retry Strategy¶

Type	Behavior
Automatic Retry	Reruns failed test up to `N` times (default: 2)
Conditional Retry	Only reruns on network, timeout, or transient conditions
Prompt-Aware Retry	For QA-triggered scenarios, retries with modified assertions
Edition-Specific Retry	Only retries failed combinations of role × edition
Feature Retry Scope	`.feature` scenario failed → rerun only that scenario, not the whole suite
Replay + Compare	Compares retry result to initial run — records delta

📁 Retry Metadata¶

trace_id: refund-2025-0143
scenario: Refund twice → error
first_result: Failed (403 expected, 200 received)
retry_count: 1
retry_successful: true
recovery_type: edition_misconfig
auto_quarantine: false

📦 Failure Triage Levels¶

Failure Type	Action
❌ Hard Failure (assertion, exception)	Mark as failed and reported in Studio, PR
🔄 Transient Error (network, timeout)	Retry up to limit
⚠️ Flaky Detected (in retry history)	Auto-quarantine or mark unstable
🧠 Prompt-Sourced Test Fails	Re-evaluate scenario accuracy + alert QA Agent
🔐 Role-Specific Misbehavior	Trigger Security Scenario Review flow
📘 Bug Trace Test Fails Again	Escalate to Bug Resolver Agent

🧱 Quarantine Process¶

sequenceDiagram
    TestRun->>RetryCheck: Detect flaky scenario
    RetryCheck-->>QuarantineStore: Flag test as unstable
    QuarantineStore->>Studio: Display warning icon
    QuarantineStore->>QAEngineerAgent: Suggest review
    TestAutomationAgent->>CI: Exclude from gate evaluation

Hold "Alt" / "Option" to enable pan & zoom

Tagged in metadata:

quarantined: true
reason: "Retried 3 times, inconsistent output"
last_verified: 2025-05-17T14:01Z

📊 Studio Display (Flaky / Quarantined)¶

Scenario	Role	Edition	Status	Retry	Quarantine
Cancel after approval	CFO	enterprise	❌	✅ success	🚫 flagged
Guest refund	Guest	lite	❌	❌	✅ quarantined

→ Users can manually retry or "unquarantine and rerun."

🧪 Retry Triggers¶

Trigger	Source
Failure pattern matched	Test result log
“Retry test” clicked in Studio	Manual trigger
Bug Resolver Agent rerun	Post-regression
New edition config pushed	Retest edition-variant scenarios
CI instability warning	Test run duration variance, memory spike

📎 Retry Reporting Summary¶

Markdown report:

### 🔁 Retry Summary for Trace: refund-2025-0143

- ❌ First run failed: Guest refund → expected 403, got 200  
- 🔁 Retried with correct edition config  
- ✅ Result: Passed on retry  
- 🧠 Trace marked as unstable (retry count = 1)  
- 📘 Added to retry-metadata.yaml + Studio warning dashboard

✅ Summary¶

The Test Automation Engineer Agent handles failures using:

🔁 Controlled, intelligent retries
🧪 Scenario-level execution granularity
📎 Trace-linked failure metadata and retry history
🧠 Auto-quarantine with Studio + QA visibility
📘 Markdown and machine-readable summaries for all retry events

This ensures the platform maintains trustworthy, reproducible, and fault-tolerant test execution — and avoids false passes or false fails.

🧩 Environment Provisioning and Configuration Injection¶

This cycle defines how the Test Automation Engineer Agent ensures that automated tests can run in consistent, isolated, and configurable environments across dev, staging, and production, supporting both infrastructure and configuration-specific automation.

🏗️ Role in the ConnectSoft Platform¶

flowchart TD
    BlueprintReady -->|Triggers| TestAutomationEngineerAgent
    TestAutomationEngineerAgent -->|Emits| TestContainersConfig
    TestContainersConfig --> CIEnvironment
    CIEnvironment -->|Executes| AutomatedTests

Hold "Alt" / "Option" to enable pan & zoom

The agent ensures that test containers, mocks, secrets, and tenant-specific runtime settings are properly initialized before executing test suites.

⚙️ Responsibilities in this Cycle¶

Area	Behavior
Container Test Environment	Use Docker/TestContainers to spin up databases, queues, and services.
Environment-Specific Config	Inject `appsettings.Development.json`, `.env.test`, or Pulumi configs.
Secrets Injection	Pull environment-specific secrets (e.g., test tokens) from Key Vault.
Feature Flag Toggle	Enable test-only scenarios via Microsoft.FeatureManagement or mocks.
Parallelization Strategy	Coordinate parallel test execution across agent pools with isolated state.

🧬 Memory & Retrieval¶

The agent retrieves:

Test container configurations from template blueprints
Runtime dependencies from execution-metadata.json
Config layers from Memory Blob or DevOps Git

It emits:

testcontainers.config.yaml
.env.test
TestRuntimeInstructions.md

🧠 Prompt Design Snippet¶

skill: ProvisionTestEnvironment
context:
  moduleId: NotificationService
  stage: CI
  tenantId: vetclinic-001
  runtime:
    db: PostgreSQL
    messaging: RabbitMQ
    env: test
  secrets: true

✅ Output Expectation¶

File	Description
`docker-compose.test.yaml`	Starts services in test mode (DB, queues, mock APIs)
`.env.test`	Injects runtime variables for test context
`appsettings.Test.json`	Overrides to support test instrumentation
`TestRuntimeInstructions.md`	Documentation for human/agent consumption

🔍 Observability & Traceability¶

Each provisioning step emits:

traceId, executionId
testEnvironmentProvisioned event
Span: setup:test-container
Log metadata: which services spun up, ports used, secrets resolved

📣 Collaboration Hooks¶

Partner Agent	Exchange
`Infrastructure Engineer`	Shares `Pulumi`, `Bicep`, or infra mocks
`DevOps Agent`	Injects generated config into CI/CD pipeline
`QA Agent`	Pulls test run config and runtime logs

🧩 Summary¶

Cycle 11 ensures that all tests run in clean, reproducible, and isolated environments, enforcing:

Config fidelity across test environments
Predictable runtime behavior with secrets and mocks
Clear, observable execution chains

🧠 Without this cycle, automated tests would become fragile, flaky, or misconfigured across tenants and stages.

🧠 Multi-Tenant Test Adaptation¶

In the ConnectSoft AI Software Factory, every test must be aware of the tenant it targets — because tenants may differ in:

🌐 Locale or language
📦 Feature flags or modules
🔐 Security policies
💳 Edition (Lite, Pro, Enterprise)
🛠️ Custom business rules (e.g., VAT, timezone logic)

The Test Automation Engineer Agent is responsible for dynamically adapting test executions to match the correct tenant context, making all test results tenant-accurate and traceable.

🧩 What Multi-Tenant Adaptation Includes¶

Aspect	Description
Tenant Context Injection	Injects tenant ID, tenant-specific config, identity providers
Edition Filtering	Runs only those tests that are applicable to a tenant's edition
Custom Rule Overrides	Activates or disables rule sets per tenant in test config
Localized Assertions	Adjusts assertion expectations (e.g., messages in `fr-FR`, `he-IL`)
Isolated Runtime Environments	Runs each tenant test in isolated state (e.g., DB per tenant)

⚙️ Configuration Strategy¶

Agent retrieves:

Tenant blueprint from tenant-manifest.yaml
Edition + feature flags from edition-config.json
Secrets and connection strings from KeyVault:{tenant}
Localization strings from tenant-locale-resources.json

Applies them before test execution, logs result as:

test_context:
  tenant_id: vetclinic-001
  edition: enterprise
  locale: en-US
  feature_flags: [EnableLateFee, AllowBulkCancel]

🧪 Test Matrix Expansion¶

Given 3 tenants:

Tenant	Edition	Locale
`vetclinic-001`	enterprise	en-US
`dentalcare-033`	lite	fr-FR
`visionplus-902`	pro	he-IL

And a .feature file for "Invoice Cancellation"

Agent executes:

3 runs × roles × scenarios
Adjusts expected error messages (localized)
Loads tenant-specific feature toggles (e.g., bulk invoice disablement)

📘 Test Metadata Per Tenant¶

trace_id: invoice-2025-0172
tenant_id: vetclinic-001
edition: enterprise
locale: en-US
role: CFO
feature_flags:
  - AllowLateInvoice
result: passed

🔄 Retry & Feedback Adaptation¶

If test fails due to tenant-specific config:

Agent logs failure reason
Adjusts config and retries
Tags result as:

root_cause: tenant_config_mismatch
resolution: dynamic_reconfig_success

📊 Studio Impact¶

Test results are grouped per tenant:

🧪 Tenant: vetclinic-001
   ✅ CFO Approves Invoice
   ✅ Guest Access Denied
   ❌ Missing VAT Scenario → Suggested by Test Generator

✅ QA engineers can toggle tenant filters in Studio to see test impact.

📎 Collaboration Hooks¶

Agent	Integration
Studio Agent	Renders per-tenant test matrix
Tenant Provisioner Agent	Provides dynamic tenant blueprint
Test Generator Agent	Suggests scenarios for uncovered tenant rules
Test Coverage Validator	Detects gaps per tenant+edition

✅ Summary¶

This cycle ensures the Test Automation Engineer Agent can run every test as if it was the tenant, providing:

🧠 Accurate rule validation
🛡️ Configuration-scoped testing
🌐 Locale- and language-aware assertions
📊 Tenant-specific observability in dashboards
✅ CI/CD trust per SaaS tenant instance

Without multi-tenant test adaptation, the factory’s SaaS coverage model would break down in real-world deployments.

🧠 Execution Observability and Traceability¶

In a platform as large and dynamic as ConnectSoft, every test execution must be observable, traceable, and audit-safe — across tenants, editions, roles, environments, and blueprints.

The Test Automation Engineer Agent emits observability signals and metadata that enable:

📊 Real-time execution tracking
🧪 Debugging of failed tests
📎 Trace-to-test lineage
🔁 Retry visibility
✅ QA validation and audit trails

📡 Observability Data Emitted¶

Data Type	Tool/Format	Description
OpenTelemetry Spans	OTel JSON	Captures start/end of test run, trace ID, role, edition
Structured Logs	`.jsonl` or `Serilog`	Logs test inputs, outputs, assertions, retries
Execution Snapshots	`execution-metadata.yaml`	Per-test result data with context
Trace Logs	`.trace.json` or `.har`	Captures test-level request/response data
Error/Retry Metadata	`retry-history.yaml`	Tracks retries, failure types, recovery paths
QA Markdown Reports	`qa-execution-report.md`	Human-readable output for Studio

🔍 Span Example (OpenTelemetry)¶

{
  "trace_id": "refund-2025-0143",
  "span_name": "ExecuteScenario:GuestCannotCancel",
  "start_time": "2025-05-17T12:00:00Z",
  "duration_ms": 428,
  "attributes": {
    "tenant": "vetclinic-001",
    "edition": "enterprise",
    "role": "Guest",
    "result": "failed",
    "expected_status": 403,
    "actual_status": 200
  }
}

→ Forwarded to centralized observability system or Studio backend.

📘 Execution Metadata YAML¶

trace_id: invoice-2025-0147
handler: CancelInvoiceHandler
role: CFO
edition: enterprise
locale: en-US
status: passed
start_time: 2025-05-17T12:01:02Z
duration: 3.4s
assertions:
  - type: status_code
    expected: 200
    actual: 200
    result: passed
retry_count: 0
trigger_source: ci:pull_request

🧪 Failure Analysis Log¶

{
  "event": "TestFailure",
  "trace_id": "invoice-2025-0147",
  "handler": "CancelInvoiceHandler",
  "role": "Guest",
  "edition": "enterprise",
  "failure_reason": "Expected status 403, got 200",
  "retried": true,
  "retry_success": false
}

→ Consumed by QA Agent, Studio dashboards, or alert systems.

📎 Traceability Practices¶

Mechanism	Description
Trace ID Tagging	All tests are linked to `trace_id` and blueprint ID
Edition/Role Tags	Included in span and metadata outputs
Scenario + Source Linking	Tracks whether test was generated via prompt, regression, or default
Test Class → Handler Mapping	Ensures reverse lookup from test → blueprint

🧠 Studio Dashboard Integration¶

✅ Per-scenario test result status
🛠 Tooltip view of retry history and test input
🔁 Visual “Play” button to re-run test with last input
📊 Test result heatmap per role × edition × trace

📣 Alerts & Diagnostics¶

Failure Type	Alert Action
❌ Role Failure	Sends Studio alert with link to replay test
🧪 Repeated Flaky Scenario	Marks test as unstable → QA review panel
🧠 Unexpected Pass/Fail Delta	Triggers regression reasoning via Bug Resolver Agent
📈 Execution Slowness	Metrics flagged for performance anomalies

✅ Summary¶

The Test Automation Engineer Agent transforms test execution into a fully observable stream of trace-aligned, role-aware, and edition-specific spans, ensuring:

📎 Every test is traceable back to its blueprint and prompt
📊 Dashboards and metrics are updated in real-time
🔁 Failures are retry-visible, auditable, and explainable
🧪 QA engineers and developers can navigate test lineage with confidence

Without this, test coverage would become opaque, and QA feedback would lack context or control.

🧠 Test Sharding and Parallel Execution Management¶

To maintain fast, scalable, and reliable execution of thousands of tests across traces, roles, editions, tenants, and environments, the Test Automation Engineer Agent implements:

🧩 Intelligent sharding and parallel execution orchestration — across CI agents, containers, or cloud test nodes.

This enables optimal use of compute resources and prevents bottlenecks in CI/CD pipelines, nightly jobs, or Studio-triggered replays.

⚙️ Key Execution Strategies¶

Strategy	Description
Sharding by Trace	Each trace ID’s test suite runs in isolation from others
Edition × Role Partitioning	Matrix split across roles and editions, each sharded independently
Scenario Chunking	Large `.feature` files split by scenario for parallelism
Test Type Segmentation	Unit, integration, and BDD tests executed in separate pools
Tenant-Aware Execution Pools	Each tenant’s tests isolated by runtime container/test cluster

🧱 Example: Sharded Matrix for a Feature¶

feature: capture_payment.feature
scenarios: 6
editions: [lite, enterprise]
roles: [Cashier, Guest]

→ Total Variants: 6 × 2 × 2 = 24
→ Shards: 6 groups × 4 shards each (by edition × role)

Each shard:

Loads a subset of tests
Injects correct edition/role config
Runs tests in isolation
Sends results back to central aggregator

🧰 Sharding Methods Supported¶

Method	Tool / Layer
Azure DevOps Parallel Jobs	Shards run as matrix jobs
Docker-Based Isolation	Each job starts a `test-runner` container per shard
Orleans-Based Agent Pool (future)	Cloud-native distributed test node orchestration
Local Threaded Runner (lite)	For small test sets or CLI-triggered runs
Kubernetes Executor (optional)	Large-scale distributed `.feature` execution via pod-per-scenario model

🔁 Dynamic Sharding Algorithm¶

Agent evaluates:

Number of test cases per dimension (role × edition × scenario)
Historical duration metrics (via test-history.json)
Retry counts (flaky = isolated)
Infrastructure constraints (max parallelism)
Priority weights (security tests run first)

And emits:

test-shard-plan.yaml
  - shard_id: 1
    trace_ids: [cancel-2025-0142]
    roles: [CFO]
    edition: enterprise
  - shard_id: 2
    trace_ids: [cancel-2025-0142]
    roles: [Guest]
    edition: lite

📊 Load Balancing Behavior¶

Rule	Action
Tests exceed 30s	Force split to separate shard
Scenario tagged `@slow`	Run on dedicated low-priority shard
Retry required	Force isolate and deprioritize
Bug trace replay	High-priority fast-track shard
Edition = `pro`, Role = `Admin`	Run on enterprise test pool nodes

📘 Runtime Metadata Per Shard¶

shard_id: 9
execution_group: refund-2025-0143
edition: enterprise
role: Guest
status: passed
retry_count: 0
duration: 7.2s
agent_instance: test-runner-shard9

→ Used by Studio to show per-scenario result timeline and heatmap.

🧠 Coordination Flow¶

flowchart TD
    Plan[Test Suite Plan]
    Plan --> Shard1[Shard A]
    Plan --> Shard2[Shard B]
    Plan --> Shard3[Shard C]
    Shard1 --> Results
    Shard2 --> Results
    Shard3 --> Results
    Results --> Aggregator[Test Result Aggregator]
    Aggregator --> Studio

Hold "Alt" / "Option" to enable pan & zoom

✅ Summary¶

The Test Automation Engineer Agent manages large-scale test execution by:

🔁 Sharding tests intelligently across roles, editions, and scenarios
⚡ Running everything in parallel, isolated, and trace-safe environments
📊 Feeding aggregated results back into Studio, PRs, and QA reports
🔧 Scaling test execution linearly as test volume grows

This is the execution engine for continuous quality across 100s of modules and 1000s of trace IDs.

🧠 Metrics, Thresholds, and Quality Gates¶

The Test Automation Engineer Agent enforces quality assurance policies by generating and emitting metrics, thresholds, and pass/fail gates that:

📊 Quantify test health across traces, roles, and editions
🚦 Enforce CI/CD safety before merges or releases
🧪 Detect regressions, flaky behavior, and coverage degradation
📘 Support automated decisions for deployment control, QA signoff, and retry triggers

📦 Core Metrics Tracked¶

Metric	Description
`test.success_rate`	% of tests passed in this shard/trace/test type
`test.retry_rate`	% of tests that needed retry
`test.flaky_rate`	Ratio of unstable tests (flaky over time)
`scenario.coverage`	Percent of blueprint scenarios executed per trace
`edition_completeness`	Edition/role matrix coverage score
`assertion_density`	Average number of assertions per test
`critical_failures`	Number of failed `@security` or `@regression` scenarios
`test.duration.avg`	Average execution time across matrix
`test.blockers`	Total tests marked as `block release`
`quarantine_count`	Number of tests flagged as unstable

🚦 Quality Gate Rules¶

Agent evaluates every test suite and emits a quality gate status:

Rule	Threshold	Action
✅ Success Rate	> 95%	Pass
⚠️ Retry Rate	< 5%	Pass
❌ Critical Failures	= 0	Required
✅ Security Scenario Pass	100%	Required for merge/release
⚠️ Test Duration (avg)	< 15s per test	Info only
❌ Quarantine Count	< 3 unstable tests	Pass
⚠️ Coverage Delta	≥ last build	Warning on drop
✅ Assertion Density	≥ 1.5 per test	Optional for observability gate

📘 Example: Quality Gate Summary (YAML)¶

trace_id: invoice-2025-0147
suite_status: failed
gate_summary:
  success_rate: 87%
  retry_rate: 8%
  critical_failures: 2
  security_pass: false
  edition_matrix_coverage: 5/6
  quarantine_count: 4
reasons:
  - "Failed: Guest scenario expected 403 but returned 200"
  - "Missing test for CFO in pro edition"
actions:
  - Suggest regenerate from Test Generator Agent
  - Rerun flaky tests in isolation

📄 Markdown QA Report Excerpt¶

### ✅ Quality Gate Result: ❌ Blocked

- 🔴 2 critical security tests failed  
- ⚠️ 4 tests flagged as flaky (quarantined)  
- 🔁 3/6 roles tested (missing: CFO, Admin, Analyst)  
- 📉 Coverage dropped from 82% → 74%  
- 🚦 CI pipeline halted (requires QA review + rerun approval)

📊 Studio Display¶

Trace	Edition	Role	Status	Gate	Coverage
`cancel-2025-0142`	enterprise	CFO	✅	✅ Pass	100%
`refund-2025-0143`	pro	Guest	❌	❌ Blocked	66%
`invoice-2025-0172`	lite	FinanceManager	✅	⚠️ Warning	90%

🔄 Gate Actions Triggered¶

Action	Trigger
🔁 Retry test	Threshold: flaky = true
🧪 Re-gen scenario	Trigger: missing role coverage
❌ Mark test unstable	Failure in 2 of last 3 builds
🚫 Block release	Critical security regression
⚠️ Show Studio alert	Coverage or quality drop from baseline

🧠 Metrics Emitted Format¶

metrics/test-results.json
test-metrics.prometheus.txt (for monitoring integration)
qa-summary.yaml
markdown-status.md

All tagged with:

trace_id, edition, role, test_type
source_agent, execution_id, retry_count

✅ Summary¶

With this cycle, the Test Automation Engineer Agent becomes the guardian of continuous quality by:

📊 Measuring execution health with rich QA metrics
🚦 Enforcing pass/fail gates at merge and release stages
🧠 Supporting Studio visibility and feedback loops
🔁 Connecting test failures to intelligent next steps (rerun, regenerate, revalidate)

Without this, test automation would become invisible and unreliable to the factory’s DevOps and QA loops.

🎯 Support for Manual and Scheduled Test Runs¶

In addition to running tests in response to CI/CD events, the Test Automation Engineer Agent must support:

🖐 Manual execution requests (e.g., via Studio or QA prompt)
📅 Scheduled jobs (e.g., nightly regressions, weekly chaos validation)
🔁 On-demand replays, edge-case runs, and exploratory test sweeps

This enables QA engineers and product owners to validate scenarios on demand, without waiting for pipeline events — ensuring continuous validation of critical business flows, long-running tests, and non-blocking coverage.

🔁 Manual Execution Use Cases¶

Scenario	Trigger Source	Action
QA reviews a bug fix	Studio → “Rerun failed scenario”	Runs exact `.feature`/`.cs` combo
Prompt-based trace generated	QA prompt in Studio	Test Generator → Agent executes immediately
Edition configuration updated	QA clicks “Retest all scenarios for `lite`”	Full matrix rerun for edition
QA validates access rule changes	Manual run scoped by role	Security test matrix re-executed

📅 Scheduled Execution Use Cases¶

Schedule Type	Example
Nightly Regressions	Run all @regression and @security scenarios
Weekly Chaos/Retry Tests	Run scenarios tagged `@retry`, `@chaos`, `@flaky`
Edition Consistency Audits	Validate functional parity between `pro` and `enterprise` editions
Tenant Health Checks	Run 5–10 core tests across all tenants nightly
Prompt Backlog Drains	Re-execute tests generated from prompt backlog that weren’t prioritized in CI

📘 Example Manual Trigger (Studio API)¶

{
  "action": "manual_execute",
  "trace_id": "invoice-2025-0172",
  "role": "CFO",
  "edition": "enterprise",
  "scenarios": ["Invoice approval denied for Guest"]
}

Agent response:

status: started
execution_id: exec-9083
trigger: studio.manual
started_by: alex.qa

🧠 Scheduled Plan Definition (YAML)¶

schedule_id: nightly-qa-core-suite
schedule: 0 2 * * *
tests:
  tags: [@core, @security]
  roles: [Admin, CFO]
  editions: [lite, pro, enterprise]
  tenants: all
notifications:
  on_failure: slack://qa-alerts
  on_complete: post_summary_to_studio

Agent loads schedule.yaml, provisions isolated runner pools, and executes across shards.

📎 Metadata for Manual/Scheduled Runs¶

trigger: manual
trigger_source: studio.qa
triggered_by: olga.qa
execution_mode: on_demand
run_id: exec-1123
trace_id: refund-2025-0188
scenario: Refund fails for CFO with locked invoice

📊 Output Location¶

Manual and scheduled results are published to:

manual-results/<run_id>/*.md
studio-trace-results/<trace_id>/<role>/<edition>/qa-execution-report.md
Studio Test History view
qa-backlog.yaml (for any tests queued due to infra limits)

✅ Summary¶

The agent supports:

🖐 Manual QA- or PM-initiated runs
📅 Repeatable scheduled test suites
🔁 Reruns by trace, role, scenario, or edition
📎 Full audit trail of who ran what, why, and when
📘 Markdown summaries and logs for human review

This gives ConnectSoft a continuous QA safety net, outside the CI/CD pipeline — supporting experimentation, confidence, and coverage.

🎯 Collaboration with QA Engineer and Coverage Validator Agents¶

To maintain complete, role-aware, edition-specific test coverage, the Test Automation Engineer Agent must actively collaborate with:

🧪 QA Engineer Agent → for test plan validation, feedback loops, and Studio integrations
📊 Test Coverage Validator Agent → for real-time measurement of what was tested and what remains untested

This triad ensures test automation is strategic, traceable, and coverage-aligned, not just reactive or mechanical.

🤝 Integration with QA Engineer Agent¶

Collaboration Mode	Description
Execution Planning	Accepts test run instructions from QA plan (`qa-plan.yaml`)
Manual Feedback Handling	Accepts QA actions from Studio (approve/reject test run, rerun scenario)
Scenario Validation Status	Reports results of manual prompt-based or critical-path tests
QA Test Gap Review	Agent emits list of failed, flaky, or missing test runs for QA to review
Studio Trace Sync	Agent populates per-scenario execution summaries to Studio dashboards

📊 Integration with Coverage Validator Agent¶

Integration Type	Description
Before Execution	Validator agent provides trace/role/edition coverage expectations
After Execution	Automation agent emits actual test run matrix and results
Gap Resolution Triggers	If gaps remain, triggers `Test Generator Agent` or suggests `QA Rerun`
Failure Clustering	Validator tags frequently failing or uncovered role-edition-scenario clusters
Delta Reporting	Agent helps generate before/after coverage heatmaps post execution

📘 Sample QA Plan Fragment (from QA Engineer Agent)¶

qa-plan:
  trace_id: capture-2025-0143
  required_roles:
    - Cashier
    - Guest
  required_editions:
    - lite
    - enterprise
  test_types:
    - bdd
    - security
  test_tags:
    - @retry
    - @prompt_generated
  must_pass:
    - Scenario: Guest cannot approve payment

The Test Automation Engineer Agent:

Executes specified matrix
Validates results and marks required must_pass scenarios
Publishes report back to QA Engineer Agent and Studio

📎 Studio Feedback Workflow¶

sequenceDiagram
    QAEngineer->>Studio: Request scenario rerun
    Studio->>TestAutomationAgent: Execute scenario(trace_id, role)
    TestAutomationAgent->>QAEngineerAgent: Report pass/fail
    QAEngineerAgent->>Studio: Update status + coverage marker

Hold "Alt" / "Option" to enable pan & zoom

📊 Sample Coverage Delta Report¶

trace_id: cancel-2025-0142
coverage_before:
  total_roles: 4
  tested: 2
coverage_after:
  tested: 4
  full_matrix_passed: true
summary: All critical paths executed successfully

→ Used by Coverage Validator and QA Engineer Agents to update QA dashboards.

🔁 Gap Remediation Loop¶

Detected By	Resolved By
QA Agent flags missing test	Test Generator Agent → Automation Agent executes
Validator detects partial role matrix	Automation Agent runs missing combinations
Automation Agent detects unexpected behavior	Opens feedback task in Studio + retry ticket

✅ Summary¶

The Test Automation Engineer Agent is not an isolated executor — it:

🤝 Aligns tightly with QA strategies via the QA Engineer Agent
📊 Closes the loop with the Coverage Validator Agent to enforce test completeness
🔁 Supports Studio-driven actions, scenario replays, and test plan validations
📎 Links every execution to feedback, regression prevention, and test health evolution

This collaborative structure turns automation into continuous quality assurance — not just test running.

🎯 Automation Metadata, Execution Snapshots, and Logs¶

Every test execution triggered by the Test Automation Engineer Agent must leave behind:

📁 A complete execution snapshot
🧾 Machine-readable metadata for CI, QA, and dashboards
📄 Human-readable summaries for Studio, QA, and documentation
🔍 Logs and error traces for reproducibility, audits, and debugging

This cycle ensures every test run is fully inspectable, self-documented, and linked back to its origin.

📦 Core Output Artifacts¶

File	Description
`test-execution-summary.yaml`	Machine-readable result per test/role/edition
`qa-execution-report.md`	Markdown summary of execution, for QA dashboards
`.trx`, `.xml`, `.json`	Framework-specific result files (MSTest, SpecFlow, etc.)
`retry-history.yaml`	Retry reason, success, retry count
`assertion-logs.jsonl`	Structured logs of what was asserted and why
`execution.env.json`	Captures the environment context (role, edition, tenant)
`test-run.trace.json`	Detailed trace of input/output pairs, responses, exceptions

🧠 Metadata Example: `test-execution-summary.yaml`¶

execution_id: exec-9034
trace_id: refund-2025-0143
handler: IssueRefundHandler
role: Guest
edition: enterprise
locale: en-US
status: passed
test_type: bdd
assertions:
  - expected: 403
    actual: 403
    type: status_code
    result: passed
duration_seconds: 4.2
retried: false
started_by: ci:pull_request

📘 Markdown Summary: `qa-execution-report.md`¶

### 🧪 Test Execution Report — refund-2025-0143

🔹 Handler: IssueRefundHandler  
🔹 Edition: Enterprise  
🔹 Role: Guest  
🔹 Locale: en-US  
🔹 Status: ✅ Passed  
🔹 Duration: 4.2s

**Scenario**: Guest tries to issue a refund  
- ✅ Status code = 403  
- ✅ Error message = "Access Denied"

📎 Trigger: CI Pull Request #4829

📂 Artifact Directory Structure¶

/test-results/
└── refund-2025-0143/
    ├── test-execution-summary.yaml
    ├── qa-execution-report.md
    ├── refund_guest_enterprise.trx
    ├── retry-history.yaml
    ├── execution.env.json
    └── assertion-logs.jsonl

📊 Log Example: `assertion-logs.jsonl`¶

{
  "trace_id": "refund-2025-0143",
  "scenario": "Guest issues refund",
  "assertion": "StatusCode == 403",
  "result": "passed",
  "duration_ms": 82
}

→ Used in Studio’s log viewer, QA diagnostic panels, and metrics dashboards.

🧩 Observability Metadata¶

Each artifact is tagged with:

trace_id, role, edition, execution_id, source, test_type
Retry info, CI build ID, and runtime env hash

📎 QA & Studio Usage¶

Purpose	Artifact
Review failed test	`qa-execution-report.md`
Debug unexpected result	`assertion-logs.jsonl`, `trace.json`
Track retry history	`retry-history.yaml`
Show test config context	`execution.env.json`
Sync dashboards	`test-execution-summary.yaml`

✅ Summary¶

This cycle ensures the Test Automation Engineer Agent emits:

📘 Human-readable summaries for Studio and QA
📊 Machine-readable metadata for CI/CD, validators, and coverage reports
🧪 Execution context, retries, and assertion logs for diagnostics
📁 Organized file structure for all test traces, failures, replays, and audits

It turns every test run into a self-contained, traceable QA asset — not just a log line in a CI server.

🎯 Error Feedback Loop — Triggering Retries, Generator Feedback, and QA Recovery¶

When a test fails, the Test Automation Engineer Agent doesn’t just log the failure — it activates an intelligent feedback loop that:

🔁 Retries recoverable tests
📤 Sends failed cases to the Test Generator Agent for patching or augmentation
🧑‍💼 Alerts the QA Engineer Agent for manual review, tagging, or regression response
🔍 Records all outcomes for traceability and future retries

This feedback loop helps ConnectSoft achieve self-healing QA across the platform.

🔁 Retry + Feedback Cycle¶

flowchart TD
    A[Test Fails] --> B[Evaluate Failure Type]
    B -->|Flaky| C[Retry]
    B -->|Assertion Mismatch| D[QA Alert + Prompt Rerun]
    B -->|Missing Scenario| E[Test Generator Agent Trigger]
    C --> F[Retry Outcome: Pass/Fail]
    D --> G[Studio Feedback]
    E --> H[Patch Scenario or Suggest Fix]

Hold "Alt" / "Option" to enable pan & zoom

🧩 Feedback Triggers¶

Condition	Feedback Action
❌ Scenario fails with missing role	Trigger `Test Generator` → emit missing role variant
❌ Invalid assertion (e.g. 200 instead of 403)	Flag Studio + QA review dashboard
🔁 Retry succeeds	Record as `flaky`, tag scenario for night audit
🚫 Retry fails again	Open “regression suspect” report in `test-regression-candidates.yaml`
🧠 Prompt-based test fails	QA may edit, refine, or regenerate test using Studio
🧾 Missing .feature coverage	`Coverage Validator` suggests expansion plan
🛠 Infra/setup issue	Create retry job + optionally skip temporarily

📘 Retry Metadata Log Example¶

trace_id: cancel-2025-0142
scenario: CFO cannot cancel paid invoice
first_attempt:
  status: failed
  actual: 200
  expected: 403
retry_attempt:
  status: passed
  reason: edition misconfigured
tag: flaky
feedback_actions:
  - notify_qa
  - quarantine_scenario
  - suggest regeneration

📣 QA Recovery Loop¶

Trigger	Action
Prompt test failed	Agent posts Studio message: "Scenario failed, review recommended."
Test removed by generator	QA notified to review gap
Retry count > threshold	QA must approve re-test or regeneration
Quarantined test	QA Engineer Agent tags with `quarantine` reason and remediation plan

📎 Generator Feedback API (Test Generator Agent)¶

{
  "trace_id": "invoice-2025-0172",
  "failure_reason": "Missing THEN clause for assertion",
  "scenario": "Guest cancels paid invoice",
  "recommendation": "Regenerate using prompt: 'What if Guest cancels after invoice paid?'"
}

→ Generator receives prompt context and trace metadata, generates patched .feature.

📊 QA Feedback View in Studio¶

Trace	Scenario	Result	Retry	Feedback
`refund-2025-0143`	Guest issues refund	❌	✅ passed on 2^nd	Tagged as flaky
`invoice-2025-0172`	Guest cancels invoice	❌	❌ failed again	Requires scenario patch

🧠 Recovery Tags Emitted¶

Tag	Meaning
`retry_success`	Passed on retry, needs observation
`flaky_scenario`	Repeat fail → QA to monitor
`regression_candidate`	Retry failed twice — feed bug resolver
`missing_variant`	Generator missed scenario
`studio_feedback_required`	QA interaction needed

✅ Summary¶

This cycle enables the Test Automation Engineer Agent to:

🔁 Automatically retry when safe
📤 Send failed tests to prompt-based regeneration
👤 Alert QA for review, retry, or reclassification
📎 Record all results, tags, and recovery plans for trace-safe feedback

It ensures the system not only detects failure, but also responds intelligently, maintaining platform-wide test resilience.

🎯 Summary and Positioning Within the QA Automation Ecosystem¶

The Test Automation Engineer Agent is the execution orchestrator and quality enforcer of the ConnectSoft AI Software Factory QA Cluster.

It ensures that:

🧪 Every test is executed in the correct role, edition, and tenant context
🚦 Quality gates, retries, and observability pipelines are enforced
📊 Studio dashboards, CI/CD pipelines, and QA engineers have full traceability
🔁 Failures are not final — they trigger remediation loops via retries, regeneration, and feedback

🧩 Position in the QA Cluster¶

flowchart TD
    A[TestCaseGeneratorAgent] --> D[TestAutomationEngineerAgent]
    B[TestGeneratorAgent] --> D
    C[CoverageValidatorAgent] --> D
    D --> E[Studio]
    D --> F[QAEngineerAgent]
    D --> G[BugResolverAgent]

Hold "Alt" / "Option" to enable pan & zoom

This agent is where static test artifacts become executable, observable validation logic.

🧪 Key Capabilities Overview¶

Capability	Description
✅ Test Execution	Unit, integration, BDD, validator, security, edition-aware
🧩 Role × Edition Matrix	Automatically expands and executes per configuration
🔁 Retry and Quarantine	Smart retries with traceability and retry logs
🛠️ Environment Provisioning	TestContainers, mocks, edition configs, tenant injection
📊 Metrics & Quality Gates	Emits coverage, success rate, instability, and blockers
📘 Observability	Span logs, metrics, YAML/JSON/Markdown reports
🧠 Collaboration	Connects with QA Agent, Test Generator, Coverage Validator
🖐 Manual Execution	Studio-triggered test runs and replays
📅 Scheduled Execution	Nightly, regression, chaos, long-running tests
📎 Feedback Loops	Sends failures to Test Generator or QA workflows for patching

📘 Outputs Summary¶

.yaml: test-execution-summary.yaml, retry-history.yaml, qa-plan-results.yaml
.jsonl: assertion logs, span traces
.md: QA-friendly test run reports
.trx/.xml: native test runner output
Studio: per-trace, per-role dashboards

⚖️ Final Comparison with Other QA Agents¶

Agent	Role
Test Case Generator Agent	Creates static unit/integration test classes
Test Generator Agent	Adds intelligent, prompt-based, edge-case test scenarios
QA Engineer Agent	Curates test plans, reviews execution, manages QA lifecycle
Test Coverage Validator Agent	Identifies gaps, coverage deltas, and audit failures
✅ Test Automation Engineer Agent	Runs tests, logs results, handles retries, and reports quality

🧠 Summary Statement¶

The Test Automation Engineer Agent is the operational heartbeat of ConnectSoft’s QA cluster — executing thousands of tests daily, maintaining coverage across tenants and editions, and continuously enforcing the platform’s observability-first, edition-aware, security-first testing principles.

Without this agent, test coverage is static and unvalidated. With it, the QA system becomes alive, intelligent, and continuously self-correcting.

🧠 Test Automation Engineer Agent Specification¶

🎯 Purpose¶

🧱 What Sets It Apart from Other QA Agents?¶

🔧 Responsibilities in Factory Flow¶

🧠 Factory Blueprint: Execution Lifecycle¶

📘 Example Responsibilities¶

🔁 Continuous Role¶

✅ Summary¶

🏗️ Strategic Role in the Factory¶

🧩 Position in Factory Cluster Topology¶

🔄 QA Engineering Cluster¶

🔁 CI/CD Pipeline Integration Points¶

🎯 Pipeline Touchpoints¶

📦 Factory Context: Service Edition & Role Flow¶

🧠 Real-Time Role in Studio¶

📘 Sample Workflow: Pull Request¶

✅ Summary¶

📋 Responsibilities¶

✅ Key Responsibilities Breakdown¶

🎯 Responsibility Scope vs. Other QA Agents¶

📘 Real-World Execution Example¶

✅ Summary¶

📥 Inputs¶

📦 Primary Inputs by Type¶

🧩 Example: test-metadata.yaml¶

🧠 Input: QA Execution Plan¶

📘 Input: Studio Manual Trigger¶

🔍 Environment Inputs¶

✅ Summary¶

📤 Outputs¶

📦 Primary Output Artifacts¶

📘 Example: Test Execution Summary¶

🧠 Markdown QA Report Output¶

📊 Observability Output (JSONL Span Log)¶

📁 File Output Directory (example)¶

📎 Traceability Metadata¶

🔄 Output Triggers for Other Agents¶

✅ Summary¶

🧪 Supported Test Types and Runners¶

📦 Supported Test Types¶

🧰 Test Runners and Tools Used¶

📘 BDD Scenario Execution¶

🧩 Execution by Scenario Tags¶

🎯 Real-World Example Execution Plan¶

✅ Summary¶

🎯 Edition- and Role-Aware Test Execution Planning¶

🧩 Key Execution Concepts¶

🧬 Execution Matrix Example¶

⚙️ How Agent Applies Edition Context¶

🔐 Role Injection Flow¶

📘 Output Metadata per Variant¶

📊 Studio Dashboard View¶

🧠 Adaptive Execution Planning¶

✅ Summary¶

🔁 Pipeline Integration (CI/CD, Pre-Merge, Release Gates)¶

🧩 Key CI/CD Integration Responsibilities¶

📘 Sample CI/CD Pipeline Structure¶

📊 Agent Output → PR Annotation Example¶

🚦 Release Gates Example¶

🧠 Pipeline-Aware Execution Scoping¶

🧾 Outputs Stored in CI¶

🧠 Studio & DevOps Integration¶

✅ Summary¶

🎯 Test Suite Composition and Selection Strategy¶

📦 What a Test Suite Consists Of¶

🧩 Strategy for Test Suite Selection¶

1. Trace-Aware Matching¶

2. Tag-Based Inclusion¶

3. Edition/Role Expansion¶

4. Change-Based Diff Scoping¶

5. QA Plan Inclusion¶

6. Bug Trace Replay¶

📘 Test Selection YAML Snapshot¶

🔍 Test Exclusion Logic¶

🎛️ Studio-Controlled Scope Override¶

✅ Summary¶

🎯 Failure Handling, Retries, and Quarantining Logic¶

🔁 Retry Strategy¶

📁 Retry Metadata¶

📦 Failure Triage Levels¶

🧩 Example: `test-metadata.yaml`¶

🧠 Metadata Example: `test-execution-summary.yaml`¶

📘 Markdown Summary: `qa-execution-report.md`¶